μ dt + σ dWt, my #$$
The simplest model of a stock price movement is that the log of the price moves in a direction, plus some noisy drift (like adding a Gaussian W𝓽 at every timestep).
Agustin Silvani gives a counterexample: Federal Open Market Committee meetings precede a volatile market episode, meaning long-term changes in μ and short-term spikes in σ come after an FOMC announcement.
“Stop hunting” by dealers and other smart-money players can sometimes shake up the price pattern ONLY during a super-short period. This occurs most in the least regulated market, FX, because dealers will pull the rug out from under their retail clients’ feet. The dealers can see their clients’ stops and will just blatantly cheat the retail clients (according to Silvani), because they only need to retain a big client’s business. (Hence it’s more profitable to cheat the small fry — there will always be more.)
Efficient markets, my #$$
Not only does this violate the Black-Scholes model (a freak σ^7 comes in and then disappears), it also violates the Strongly Efficient Market Hypothesis, which says that market price—at any instant—reflects all available information and are the best measure of the “true” value of an asset. You would obviously get a more accurate valuation from taking a one-hour average than from relying on any instantaneous price, in the above graph.
According to Silvani’s story, the dealers are very efficient at bilking worse-informed or less-experienced participants, but don’t use this as a Prediction Market!